Privacy-preserving discovery of topic-based events from social sensor signals: An experimental study on twitter
Nguyen, Duc Thanh and Jung, JE 2014, Privacy-preserving discovery of topic-based events from social sensor signals: An experimental study on twitter, The Scientific World Journal, vol. 2014, pp. 1-5, doi: 10.1155/2014/204785.
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Privacy-preserving discovery of topic-based events from social sensor signals: An experimental study on twitter
Social network services (e.g., Twitter and Facebook) can be regarded as social sensors which can capture a number of events in the society. Particularly, in terms of time and space, various smart devices have improved the accessibility to the social network services. In this paper, we present a social software platform to detect a number of meaningful events from information diffusion patterns on such social network services. The most important feature is to process the social sensor signal for understanding social events and to support users to share relevant information along the social links. The platform has been applied to fetch and cluster tweets from Twitter into relevant categories to reveal hot topics.
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.
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